Comprehensive characterization of multiple components and metabolites of Xiaojin Capsule based on ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.
Xiaopo QiXinyu WangTaofang ChengQiuling WuNan MiXuemei MuXin GuoGang ZhaoZhijun HuangRan WuWeidong ZhangPublished in: Journal of separation science (2019)
Xiaojin Capsule, a classic traditional Chinese medicine formula, has been used to treat mammary cancer, thyroid nodules, and hyperplasia of the mammary glands. However, its systematic chemical information remained unclear, which hindered the interpretation of the pharmacology and the mechanism of action of this drug. In this research, an ultra high performance liquid chromatography coupled with a quadrupole time-of-flight mass spectrometry method was developed to identify the complicated components and metabolites of Xiaojin Capsule. Two acquisition modes, including the MSEnergy mode and fast data directed acquisition mode, were utilized for chemical profiling. As a result, 156 compounds were unambiguously or tentatively identified by comparing their retention times and mass spectrometry data with those of reference standards or literature. After the oral administration of Xiaojin Capsule, 53 constituents, including 24 prototype compounds and 29 metabolites, were detected in rat plasma. The obtained results were beneficial for a better understanding of the therapeutic basis of Xiaojin Capsule. A high-resolution and efficient separation method was firstly established for systematically characterizing the compounds of Xiaojin Capsule and the associated metabolites in vivo, which could be helpful for quality control and pharmacokinetic studies of this medicine.
Keyphrases
- tandem mass spectrometry
- ultra high performance liquid chromatography
- liquid chromatography
- mass spectrometry
- high resolution mass spectrometry
- high performance liquid chromatography
- gas chromatography
- high resolution
- ms ms
- simultaneous determination
- solid phase extraction
- quality control
- systematic review
- electronic health record
- papillary thyroid
- emergency department
- healthcare
- social media
- health information
- lymph node metastasis
- capillary electrophoresis
- squamous cell
- deep learning